models.py 文件源码

def feature_extract_net(self, lr_image):
        end_points = {}
        with slim.arg_scope([slim.conv2d, slim.conv2d_transpose], 
                           activation_fn = lrelu,
                           ):
            conv = slim.conv2d(lr_image, self.nfc, [3,3], scope = 'conv1') 
            for l in range(self.level):
                for d in range(self.depth):
                    conv = slim.conv2d(conv, self.nfc, [3,3], scope = 'conv_%d_level_%d'%(l,d))
                conv = slim.conv2d_transpose(conv, self.nfc, [4,4], stride = 2, scope = 'residual_level_%d'%(l))
                conv = slim.conv2d(conv, 3, [3,3], activation_fn = None, scope = 'conv_level_%d'%(l))
                end_points['residual_level_%d'%(l)] = conv
        return end_points